the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 17 Jun 2021
Hydrological Drought across Peninsular Malaysia: Implication of drought index
Abstract. Drought is considered a damaging natural disaster for economic, societal, and ecological impacts. The challenge of drought is to determine the drought characteristics, frequency, duration and severity, vital for drought's impact control and mitigation strategies. This paper adopts the spatial pattern of Streamflow Drought Index (SDI) for three, six, nine and twelve months for the tropical climate at Peninsular Malaysia. About 40 years of daily streamflow data based on 42 hydrological discharge stations were analyzed to obtain these indices. The area under drought stress during the study period at different time scales is stable and approximately 24 % of the total area. The years 1997–1999, 2002 and 2016–2018 mark the most critical drought years, with more than 48 % of the entire basin area under hydrological drought. According to the spatial evaluation of drought characteristics, short-term droughts are frequent in most regions, with relatively high severity and frequency in Northeast and Southeast of Peninsular Malaysia, where the maximum frequency reached 35.7 % and 42.8 %, respectively. This outcome emphasizes the importance and necessity of the basin's drought action strategies. Early detection of a probable hydrological drought can improve in the implementation of drought prevention or mitigation strategies.
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Interactive discussion
Status: closed
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RC1: 'Comment on nhess-2021-176', Marios Spiliotopoulos, 25 Jun 2021
The presented information are comprehensice and explanatory. It seems that the abstract is good enough for the scope of the special issue Recent advances in drought and water scarcity monitoring, modelling, and forecasting.
Citation: https://doi.org/10.5194/nhess-2021-176-RC1 -
AC1: 'Reply on RC1', Hasrul Hazman Hasan, 02 Aug 2021
Dear Marios Spiliotopoulos (Referee),
We would like to thank you for your comments and appreciate your support in our paper.
Citation: https://doi.org/10.5194/nhess-2021-176-AC1
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AC1: 'Reply on RC1', Hasrul Hazman Hasan, 02 Aug 2021
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RC2: 'Comment on nhess-2021-176', Anonymous Referee #2, 06 Jul 2021
General comment
The manuscript illustrates the application of a standard hydrological drought index (Streamflow Drought Index, SDI) for the detection at the regional scale of drought events; the case study is the peninsular Malaysia. This work contributes to the state of the art on the topic by improving the knowledge about the hydrology of the case study region. The topic is of interest for the hydrologic community, yet the manuscript needs additional efforts from the Authors to clarify some aspects that are fundamental for the reader understanding; further, a deeper analysis based on the available data is expected. Specific comments follow.
Specific comments
- From the abstract alone it is not clear which is the content and main objective of this work; further, it appears that this work is simply a case study application of methods already known in the literature. If this is true, it should be emphasized the innovative contribution provided by this work.
- Also the Introduction Section needs additional efforts from the Authors to better state the research gaps that justify the proposed work and to avoid repetitions. I’m not sure that the literature review covers properly what has been already proposed in the literature in terms of drought indexes development and application. Further, while the Authors states that there are not many work on SDI (l. 108-109), they report a non negligible number of reference on its application at several time-scales (l. 151-156).
- It is not clear which is the motivation for the choice of the period within the year where SDI is computed, starting in January and covering 3, 6, 9 and 12 months (l. 165-67). In other words, its should be explained why, e.g., the 9-months SDI refers to the period from January to September and not to another one (e.g. from April to December).
- SDI is an index that allows to detect drought events when it is below a given threshold value. To compute drought frequency it should be first defined a drought event; hence, section 2.3 should follow 2.4.
- Why depicting results averaged over 10-years time windows? Which is the difference between depicting the number of droughts and the frequency of drought events? Which is the statistical significance of frequency computed over a short time period of 10 years? I personally believe that the presentation of results should be improved and more details should be added.
- Drought events can be quantified (as indicated in the Methodology Section) in terms of three different quantities, intensity, duration and severity. How do those quantities are used here to understand drought phenomenon over Malaysia? I personally believe that available data are not exploited enough for drought understanding.
- Results are presented in detail yet not discussed in terms of possible physical explanation of the observed phenomenon. Hydrological droughts result from different processes, as clearly mentioned in the introduction section; yet, there is not reference to such processes.
Citation: https://doi.org/10.5194/nhess-2021-176-RC2 - AC2: 'Reply on RC2', Hasrul Hazman Hasan, 17 Aug 2021
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RC3: 'Comment on nhess-2021-176', Anonymous Referee #3, 10 Jul 2021
General Comments
The manuscript is investigating hydrological drought in Malaysia employing the Streamflow Drought Index and the run theory, which is of interest to the Journal’s audience. However, since both techniques are established, the authors should emphasize the significance and the contribution of their work. In addition, there are technical issues that the authors need to rectify in order for the analysis to be accurate. The language of the manuscript needs some improvement. My evaluation is that the manuscript does not meet NHESS’s scientific quality standards and I suggest rejection of the manuscript or conditional acceptance after major revisions.
Specific Comments
- In the introduction, the authors need to create a narrative, based on pertinent literature, that explains the contribution of their study to the reader. Lines 71-80 do not contribute towards this goal. Information about SDI in different regions does not need to be included with such detail. On the contrary, the authors need to cite and elaborate on drought studies for Malaysia in order to establish what is the new knowledge that this study is offering.
- Malaysia has a high hydropower potential and several dams (including ones for storage) constructed since the 1960s until recently. The authors also mention at lines 91-93 that seven dams had significantly lower water levels due to drought conditions in 2016. Have the authors performed flow naturalization to remove the effects of upstream flow regulations for the gauges that have a dam upstream? If no, why? For the provided figures it is not clear if there are dams upstream of the gauges. Anthropogenic interventions need to be excluded if the authors intend to evaluate how hydrological drought characteristics have changed throughout the study period. In addition, this comment is critical for the spatial analysis of hydrological drought characteristics across Malaysia.
- Based on run theory and the authors' definition of drought characteristics, drought severity is equal to the shaded area below the threshold --- here set to −1 --- (Yevjevich 1967), not the shaded area below the horizontal axis. Equation 4 should reflect that. The analysis needs to be redone.
- The authors at Line 135 state that they include in their analysis 42 gauge stations with 40 years of continuous streamflow data. In line 141 the authors state that 17 of those have a record of less than 40 years. However, Table 2 indicates that there are 12 stations with less than 30 years of record, with the smallest time series being just 12 years. It is recommended to have a record of 30 years or more to accurately compute a standardized drought index (e.g. SPI, SDI, etc.). Nalbantis & Tsakiris (2009) used a record of 30 years. The gauges with data less than 30 years need to be dropped from the analysis.
- I second the comment of Anonymous Referee #2 about what the results section is missing.
Citation: https://doi.org/10.5194/nhess-2021-176-RC3 - AC3: 'Reply on RC3', Hasrul Hazman Hasan, 17 Aug 2021
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RC4: 'Comment on nhess-2021-176', Anonymous Referee #4, 12 Jul 2021
This study aims at investigating the spatial and temporal variations of hydrological drought in Peninsular Malaysia for the period 1978-2018 by Streamflow Drought Index (SDI) using streamflow data recorded at 42 stations. The drought was also characterized at four time scales of 3-, 6-, 9- and 12-month.
1- My main concern is on the novelty of this work, especially when it was submitted to the special issue “Recent advances in drought and water scarcity monitoring, modelling, and forecasting”. Hydrological drought was characterized by Streamflow Drought Index (SDI) as developed by Nalbantis & Tsakiris (2009) without any modification. Drought characteristics were identified by the run theory (Yevjevich 1967) and the interpolation was done by the well-known Inverse Distance Weighting (IDW) method.
2- L147-149: “ The main advantage of SDI is that it requires fewer data than other indices, such as the Palmer Hydrological Drought Index, which need streamflow and rainfall data. The selection of SDI is because of the availability of streamflow data.” Does it mean rainfall data are not available in Peninsular Malaysia? In addition, as mentioned in lines 64-66 of the manuscript “several indices are using only streamflow data, namely, Regional Streamflow Deficiency Index (RSDI), Standardized Streamflow Index (SSFI), Streamflow Drought Index (SDI), Baseflow Index (BFI) and Regional Drought Area Index (RDAI)”. Why was the SDI used here?
L107: “Due to the scarcity of research on hydrological drought monitoring using SDI”. In Peninsular Malaysia? Because there are several studies using SDI in other parts of the world that were not cited in the paper. Have all the above indices been used before in Peninsular Malaysia?
Minor comments:
L82-85: It implies that the El Nino event in the year 1997-1998 was caused by climate change. If so, a reference is needed. If not, revise.
L157: “For a relatively more detailed drought index, the SDI can be computed based on the monthly streamflow value”. Most of the drought indices use monthly or smaller-scale data.
L472: “For tropical regions, it is the most sensitive scale to alterations in streamflow.” Isn’t it the case everywhere because of the smoothing effect at longer scales?
Citation: https://doi.org/10.5194/nhess-2021-176-RC4 - AC4: 'Reply on RC4', Hasrul Hazman Hasan, 17 Aug 2021
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RC5: 'Comment on nhess-2021-176', Anonymous Referee #5, 14 Jul 2021
This paper attempts to deal with a very difficult issue which is drought monitoring. The authors used only one index [Streamflow Drought Index (SDI)] for monitoring drought across Peninsular Malaysia.
I have many concerns regarding the appropriateness of this manuscript for publication in this high-impact journal and especially in the special issue “Recent advances in drought and water scarcity monitoring, modeling, and forecasting”. The specific manuscript was presented with no innovative point of view regarding the advantages in the topic of the SI. The contribution of this research in the literature is very weak and unclear. Specifically, the authors used the well-known SDI drought index and simply discussed the results.
The paper seems to be more a technical report than a research paper and this can be obvious concerning the structure and the results of this work. Also, the proposed approach seems to have strong local applicability.The authors should highlight the contribution of their work in regards to the previously published works. Also, the authors should mention extra information about the existence or not of drought early warning systems across Peninsular Malaysia. What about the flash drought monitoring processes in the study area?
Citation: https://doi.org/10.5194/nhess-2021-176-RC5 - AC5: 'Reply on RC5', Hasrul Hazman Hasan, 17 Aug 2021
Interactive discussion
Status: closed
-
RC1: 'Comment on nhess-2021-176', Marios Spiliotopoulos, 25 Jun 2021
The presented information are comprehensice and explanatory. It seems that the abstract is good enough for the scope of the special issue Recent advances in drought and water scarcity monitoring, modelling, and forecasting.
Citation: https://doi.org/10.5194/nhess-2021-176-RC1 -
AC1: 'Reply on RC1', Hasrul Hazman Hasan, 02 Aug 2021
Dear Marios Spiliotopoulos (Referee),
We would like to thank you for your comments and appreciate your support in our paper.
Citation: https://doi.org/10.5194/nhess-2021-176-AC1
-
AC1: 'Reply on RC1', Hasrul Hazman Hasan, 02 Aug 2021
-
RC2: 'Comment on nhess-2021-176', Anonymous Referee #2, 06 Jul 2021
General comment
The manuscript illustrates the application of a standard hydrological drought index (Streamflow Drought Index, SDI) for the detection at the regional scale of drought events; the case study is the peninsular Malaysia. This work contributes to the state of the art on the topic by improving the knowledge about the hydrology of the case study region. The topic is of interest for the hydrologic community, yet the manuscript needs additional efforts from the Authors to clarify some aspects that are fundamental for the reader understanding; further, a deeper analysis based on the available data is expected. Specific comments follow.
Specific comments
- From the abstract alone it is not clear which is the content and main objective of this work; further, it appears that this work is simply a case study application of methods already known in the literature. If this is true, it should be emphasized the innovative contribution provided by this work.
- Also the Introduction Section needs additional efforts from the Authors to better state the research gaps that justify the proposed work and to avoid repetitions. I’m not sure that the literature review covers properly what has been already proposed in the literature in terms of drought indexes development and application. Further, while the Authors states that there are not many work on SDI (l. 108-109), they report a non negligible number of reference on its application at several time-scales (l. 151-156).
- It is not clear which is the motivation for the choice of the period within the year where SDI is computed, starting in January and covering 3, 6, 9 and 12 months (l. 165-67). In other words, its should be explained why, e.g., the 9-months SDI refers to the period from January to September and not to another one (e.g. from April to December).
- SDI is an index that allows to detect drought events when it is below a given threshold value. To compute drought frequency it should be first defined a drought event; hence, section 2.3 should follow 2.4.
- Why depicting results averaged over 10-years time windows? Which is the difference between depicting the number of droughts and the frequency of drought events? Which is the statistical significance of frequency computed over a short time period of 10 years? I personally believe that the presentation of results should be improved and more details should be added.
- Drought events can be quantified (as indicated in the Methodology Section) in terms of three different quantities, intensity, duration and severity. How do those quantities are used here to understand drought phenomenon over Malaysia? I personally believe that available data are not exploited enough for drought understanding.
- Results are presented in detail yet not discussed in terms of possible physical explanation of the observed phenomenon. Hydrological droughts result from different processes, as clearly mentioned in the introduction section; yet, there is not reference to such processes.
Citation: https://doi.org/10.5194/nhess-2021-176-RC2 - AC2: 'Reply on RC2', Hasrul Hazman Hasan, 17 Aug 2021
-
RC3: 'Comment on nhess-2021-176', Anonymous Referee #3, 10 Jul 2021
General Comments
The manuscript is investigating hydrological drought in Malaysia employing the Streamflow Drought Index and the run theory, which is of interest to the Journal’s audience. However, since both techniques are established, the authors should emphasize the significance and the contribution of their work. In addition, there are technical issues that the authors need to rectify in order for the analysis to be accurate. The language of the manuscript needs some improvement. My evaluation is that the manuscript does not meet NHESS’s scientific quality standards and I suggest rejection of the manuscript or conditional acceptance after major revisions.
Specific Comments
- In the introduction, the authors need to create a narrative, based on pertinent literature, that explains the contribution of their study to the reader. Lines 71-80 do not contribute towards this goal. Information about SDI in different regions does not need to be included with such detail. On the contrary, the authors need to cite and elaborate on drought studies for Malaysia in order to establish what is the new knowledge that this study is offering.
- Malaysia has a high hydropower potential and several dams (including ones for storage) constructed since the 1960s until recently. The authors also mention at lines 91-93 that seven dams had significantly lower water levels due to drought conditions in 2016. Have the authors performed flow naturalization to remove the effects of upstream flow regulations for the gauges that have a dam upstream? If no, why? For the provided figures it is not clear if there are dams upstream of the gauges. Anthropogenic interventions need to be excluded if the authors intend to evaluate how hydrological drought characteristics have changed throughout the study period. In addition, this comment is critical for the spatial analysis of hydrological drought characteristics across Malaysia.
- Based on run theory and the authors' definition of drought characteristics, drought severity is equal to the shaded area below the threshold --- here set to −1 --- (Yevjevich 1967), not the shaded area below the horizontal axis. Equation 4 should reflect that. The analysis needs to be redone.
- The authors at Line 135 state that they include in their analysis 42 gauge stations with 40 years of continuous streamflow data. In line 141 the authors state that 17 of those have a record of less than 40 years. However, Table 2 indicates that there are 12 stations with less than 30 years of record, with the smallest time series being just 12 years. It is recommended to have a record of 30 years or more to accurately compute a standardized drought index (e.g. SPI, SDI, etc.). Nalbantis & Tsakiris (2009) used a record of 30 years. The gauges with data less than 30 years need to be dropped from the analysis.
- I second the comment of Anonymous Referee #2 about what the results section is missing.
Citation: https://doi.org/10.5194/nhess-2021-176-RC3 - AC3: 'Reply on RC3', Hasrul Hazman Hasan, 17 Aug 2021
-
RC4: 'Comment on nhess-2021-176', Anonymous Referee #4, 12 Jul 2021
This study aims at investigating the spatial and temporal variations of hydrological drought in Peninsular Malaysia for the period 1978-2018 by Streamflow Drought Index (SDI) using streamflow data recorded at 42 stations. The drought was also characterized at four time scales of 3-, 6-, 9- and 12-month.
1- My main concern is on the novelty of this work, especially when it was submitted to the special issue “Recent advances in drought and water scarcity monitoring, modelling, and forecasting”. Hydrological drought was characterized by Streamflow Drought Index (SDI) as developed by Nalbantis & Tsakiris (2009) without any modification. Drought characteristics were identified by the run theory (Yevjevich 1967) and the interpolation was done by the well-known Inverse Distance Weighting (IDW) method.
2- L147-149: “ The main advantage of SDI is that it requires fewer data than other indices, such as the Palmer Hydrological Drought Index, which need streamflow and rainfall data. The selection of SDI is because of the availability of streamflow data.” Does it mean rainfall data are not available in Peninsular Malaysia? In addition, as mentioned in lines 64-66 of the manuscript “several indices are using only streamflow data, namely, Regional Streamflow Deficiency Index (RSDI), Standardized Streamflow Index (SSFI), Streamflow Drought Index (SDI), Baseflow Index (BFI) and Regional Drought Area Index (RDAI)”. Why was the SDI used here?
L107: “Due to the scarcity of research on hydrological drought monitoring using SDI”. In Peninsular Malaysia? Because there are several studies using SDI in other parts of the world that were not cited in the paper. Have all the above indices been used before in Peninsular Malaysia?
Minor comments:
L82-85: It implies that the El Nino event in the year 1997-1998 was caused by climate change. If so, a reference is needed. If not, revise.
L157: “For a relatively more detailed drought index, the SDI can be computed based on the monthly streamflow value”. Most of the drought indices use monthly or smaller-scale data.
L472: “For tropical regions, it is the most sensitive scale to alterations in streamflow.” Isn’t it the case everywhere because of the smoothing effect at longer scales?
Citation: https://doi.org/10.5194/nhess-2021-176-RC4 - AC4: 'Reply on RC4', Hasrul Hazman Hasan, 17 Aug 2021
-
RC5: 'Comment on nhess-2021-176', Anonymous Referee #5, 14 Jul 2021
This paper attempts to deal with a very difficult issue which is drought monitoring. The authors used only one index [Streamflow Drought Index (SDI)] for monitoring drought across Peninsular Malaysia.
I have many concerns regarding the appropriateness of this manuscript for publication in this high-impact journal and especially in the special issue “Recent advances in drought and water scarcity monitoring, modeling, and forecasting”. The specific manuscript was presented with no innovative point of view regarding the advantages in the topic of the SI. The contribution of this research in the literature is very weak and unclear. Specifically, the authors used the well-known SDI drought index and simply discussed the results.
The paper seems to be more a technical report than a research paper and this can be obvious concerning the structure and the results of this work. Also, the proposed approach seems to have strong local applicability.The authors should highlight the contribution of their work in regards to the previously published works. Also, the authors should mention extra information about the existence or not of drought early warning systems across Peninsular Malaysia. What about the flash drought monitoring processes in the study area?
Citation: https://doi.org/10.5194/nhess-2021-176-RC5 - AC5: 'Reply on RC5', Hasrul Hazman Hasan, 17 Aug 2021
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Cited
3 citations as recorded by crossref.
- Spatiotemporal variability assessment and accuracy evaluation of Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index in Malaysia Y. Tan et al. 10.1007/s12145-022-00921-5
- Improving multi-month hydrological drought forecasting in a tropical region using hybridized extreme learning machine model with Beluga Whale Optimization algorithm M. Hameed et al. 10.1007/s00477-023-02548-4
- Characterization and assessment of hydrological droughts using GloFAS streamflow data for the Narmada River Basin, India S. Swain et al. 10.1007/s11356-023-27036-8